Statistical machine translation systems generate translations on the basis of statistical models derived from an analysis of bilingual text. In particular, text segments can be translated based upon a probability distribution that a segment in a target language (e.g. Spanish) is a translation of a segment in a source language (e.g. English). While conventional statistical machine translations can provide translations of a reasonable quality, there remains room for improvement in the quality of translations generated by such systems.
Additionally, in some use cases for statistical machine translation systems, additional training data can become available after the machine translation system has been trained and deployed for use in translating text. In these use cases, the additional training data can be utilized to retrain the machine translation system. Conventional statistical machine translation systems can, however, require a significant amount of time to retrain with additional training data.
The disclosure made herein is presented with respect to these and other considerations.